Project - Developing Data Products

Project Goals

-Take a look how some Canadian provinces’ population changed overtime
-Take a look at some regression about what affects the Canadian GNI per capita

Population eh!

Codes for interactive map generation

prov.pop <- fread("./can_pop.csv",stringsAsFactors = FALSE)

colnames(prov.pop)[1] <- "Province"

prov.pop[] <- lapply(prov.pop, function(x) gsub(",","",x))

prov.pop[] <- lapply(prov.pop, function(x) as.character(x))
prov.pop[,2:272] <- lapply(prov.pop[,2:272], function(x) as.numeric(x))

region <- readOGR("./src/ref/ne_50m_admin_1_states_provinces_lakes", encoding='UTF-8')


prov.pop %>% leaflet() %>% 
    addTiles() %>% 
    setView(-100, 62,  zoom = 3) %>% 
    addPolygons(data = subset(region, name %in% c("Quebec","British Columbia", "Alberta", "Saskatchewan", "Manitoba", "Ontario", "Quebec", "New Brunswick", "Prince Edward Island", "Nova Scotia", "Newfoundland and Labrador", "Yukon", "Northwest Territories", "Nunavut")), 
                fillColor = topo.colors(15, alpha = NULL),
                weight = 1) %>%
    addCircles(popup = paste0(prov.pop$Province),
               weight = 4,
               radius = (prov.pop$`1952 Q1`)*.015,color = "red")

Population eh!

The shiny app will have a slider to change the quarter of the year and the population change, represented by the size of the circle, will change.

+−

Leaflet | © OpenStreetMap contributors, CC-BY-SA

Summary aqnd plot of the linear regression model for GNI per capita

Data: World Bank Databank

Values were converted into logarithm form first

Summary

Call:
lm(formula = GNI ~ . - Year, data = indicator.1)

Residuals:
      Min        1Q    Median        3Q       Max 
-0.081389 -0.017057  0.001302  0.024043  0.072976 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -10.41019    0.37103 -28.058  < 2e-16 ***
EXP          -0.38919    0.09553  -4.074 0.000195 ***
IMP           0.54996    0.12463   4.413 6.75e-05 ***
CONS         -0.22028    0.21774  -1.012 0.317356    
GEXP          0.65077    0.17751   3.666 0.000673 ***
INV           0.20923    0.05560   3.763 0.000503 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.03616 on 43 degrees of freedom
Multiple R-squared:  0.9976,    Adjusted R-squared:  0.9973 
F-statistic:  3562 on 5 and 43 DF,  p-value: < 2.2e-16

Plot